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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: w2v2-base-pretrained_lr5e-5_at0.2_da1
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # w2v2-base-pretrained_lr5e-5_at0.2_da1
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0942
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+ - Wer: 0.1674
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - training_steps: 4000
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 17.4656 | 3.91 | 250 | 3.8210 | 1.0 |
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+ | 3.2203 | 7.81 | 500 | 3.1655 | 1.0 |
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+ | 2.5403 | 11.72 | 750 | 1.2547 | 0.9979 |
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+ | 0.5746 | 15.62 | 1000 | 0.5996 | 0.5088 |
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+ | 0.2573 | 19.53 | 1250 | 0.7483 | 0.2046 |
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+ | 0.152 | 23.44 | 1500 | 0.9229 | 0.1862 |
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+ | 0.1082 | 27.34 | 1750 | 0.9192 | 0.1833 |
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+ | 0.0748 | 31.25 | 2000 | 1.0565 | 0.1747 |
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+ | 0.0603 | 35.16 | 2250 | 0.9710 | 0.1815 |
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+ | 0.0485 | 39.06 | 2500 | 1.0599 | 0.1704 |
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+ | 0.0399 | 42.97 | 2750 | 1.0942 | 0.1730 |
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+ | 0.034 | 46.88 | 3000 | 1.0842 | 0.1670 |
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+ | 0.0309 | 50.78 | 3250 | 1.0670 | 0.1632 |
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+ | 0.0269 | 54.69 | 3500 | 1.1369 | 0.1649 |
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+ | 0.0244 | 58.59 | 3750 | 1.0229 | 0.1666 |
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+ | 0.0228 | 62.5 | 4000 | 1.0942 | 0.1674 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.0.0
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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